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Colloidal building blocks with re-configurable shapes and dynamic interactions can exhibit unusual self-assembly behaviors and pathways. In this work, we consider the phase behavior of colloids coated with surface-mobile polymer brushes that behave as "dynamic surfactants." Unlike traditional polymer-grafted colloids, we show that colloids coated with dynamic surfactants can acquire anisotropic macroscopic assemblies, even for spherical colloids with isotropic attractive interactions. We use Brownian Dynamics simulations and dynamic density functional theory to demonstrate that time-dependent reorganization of the dynamic surfactants leads to phase diagrams with anisotropic assemblies. We observed that the microscopic polymer distributions impose unique geometric constraints between colloids that control their packing into lamellar, string, and vesicle phases. Our work may help discover versatile building blocks and provide extensive design freedom for assembly out of thermodynamic equilibrium. [ABSTRACT FROM AUTHOR]

We combine on-the-fly trajectory surface hopping simulations and the doorway–window representation of nonlinear optical response functions to create an efficient protocol for the evaluation of time- and frequency-resolved fluorescence (TFRF) spectra and anisotropies of the realistic polyatomic systems. This approach gives the effective description of the proper (e.g., experimental) pulse envelopes, laser field polarizations, and the proper orientational averaging of TFRF signals directly from the well-established on-the-fly nonadiabatic dynamic simulations without extra computational cost. To discuss the implementation details of the developed protocol, we chose cis-azobenzene as a prototype to simulate the time evolution of the TFRF spectra governed by its nonadiabatic dynamics. The results show that the TFRF is determined by the interplay of several key factors, i.e., decays of excited-state populations, evolution of the transition dipole moments along with the dynamic propagation, and scaling factor of the TFRF signals associated with the cube of emission frequency. This work not only provides an efficient and effective approach to simulate the TFRF and anisotropies of realistic polyatomic systems but also discusses the important relationship between the TFRF signals and the underlining nonadiabatic dynamics. [ABSTRACT FROM AUTHOR]

This article presents methodological advances in the state-of-the-art for making time-dependent, thermochemical measurements within kilogram-scale explosive post-detonation fireballs utilizing tunable laser absorption spectroscopy. This measurement capability is critical for validating multi-scale, multi-physics models of post-detonation dynamics. The technique is based on hardened gauges built around rapidly-tunable lasers and custom post-processing algorithms that provide quantitative thermochemical data interior to large and opaque explosive fireballs. The authors present a holistic overview of the technique including gauge design, the laser absorption diagnostic, and the custom data processing algorithms. Additionally, fielding high-bandwidth laser absorption probes at stand-off ranges presents new challenges in data processing that must compensate for long distance signal transmission effects. We highlight representative data from a hardened gauge measurement at 0.81 m stand-off from a 2.78 kg LX-14 explosive charge detonated in an outdoor test arena. We discuss progress in all-optical measurement of temperature, pressure, and water vapor number density at a 100 kHz repetition rate during the first 10 ms of the fireball evolution. We conclude the article with a brief discussion on our current approach for comparing hardened gauge measurements with computational fluid dynamic simulations. [ABSTRACT FROM AUTHOR]

Modelling of many real-world processes, such as drug delivery, wastewater treatment, and pharmaceutical production, requires accurate descriptions of the dynamics of hard particles confined in complicated domains. In particular, when modelling sedimentation processes or systems with driven flows, it is important to accurately capture volume exclusion effects. This work applies Dynamic Density Functional Theory to the evolution of a particle density under diffusion, external forces, particle–particle interaction, and volume exclusion. Using a spectral element framework, for the first time it is possible to include all of these effects in dynamic simulations on complex domains. Moreover, this allows one to apply complicated no-flux, and other non-local, non-linear, boundary conditions. The methodology is also extended to control problems, addressing questions of how to enhance production set-up in industrially-motivated processes. In this work the relevant models are introduced, numerical methods are discussed, and several example problems are solved to demonstrate the methods' versatility. It is shown that incorporating volume exclusion is crucial for simulation accuracy and we illustrate that the choice of boundary conditions significantly impacts the dynamics. [ABSTRACT FROM AUTHOR]

Parkinson's disease is accompanied by the presence of amyloids in the brain that are formed of α-synuclein chains. The correlation between COVID-19 and the onset of Parkinson's disease led to the idea that amyloidogenic segments in SARS-COV-2 proteins can induce aggregation of α-synuclein. Using molecular dynamic simulations, we show that the fragment FKNIDGYFKI of the spike protein, which is unique for SARS-COV-2, preferentially shifts the ensemble of α-synuclein monomer toward rod-like fibril seeding conformations and, at the same time, differentially stabilizes this polymorph over the competing twister-like structure. Our results are compared with earlier work relying on a different protein fragment that is not specific for SARS-COV-2. [ABSTRACT FROM AUTHOR]

The traditional 70 MPa liquid hydrogen (LH 2) refueling stations (HRSs) require LH 2 pumps with high outlet pressures, leading to high initial investment, energy consumption, and difficulty in developing an LH 2 pump meeting requirements. Existing LH 2 HRSs using thermal compression eliminate the need for pressurization equipment but result in significant waste due to low-pressure hydrogen venting. Therefore, we have pioneered a novel pump-thermal synergistic pressurization process for an efficient LH 2 HRS system. The process utilizes a 45 MPa LH 2 pump and an electric heating method, allowing easily controllable heat input. This study constructs a thermodynamic model for this system that includes the dynamic operational processes of all core components. Based on the established model, the outlet parameters of the LH 2 pump, characteristic parameters of the pressure vessel, the refueling process, and the operation of the entire system are investigated. By dynamic simulation of the whole HRS system with pump and thermal compression, it is found that the specific energy consumption for hydrogen refueling is reduced to 0.55 kWh/kg, with the pump consuming 0.2 kWh/kg while thermal compression consuming 0.35 kWh/kg. After optimizing control strategies, the cycle venting of the pressure vessel and the residual hydrogen gas after re-heating and pressurization account for only 11.6%, and further utilization through the pump pressurization cycle can achieve high utilization with no residuals. This system effectively reduces the initial investment and energy consumption for LH 2 HRSs. It simplifies the structure, facilitating the retrofit of existing stations and promoting the construction and application of HRSs. [Display omitted] • An advanced hydrogen refueling station with pump and thermal compression is proposed. • A simulation model is developed for HRS with pump and thermal compression. • Thermodynamic analysis of HRS with pump and thermal compression is conducted. [ABSTRACT FROM AUTHOR]

With the aim of finding the plant-derived allosteric inhibitors of caspase-3/-7, we conducted computational investigations of bioactive compounds present in various berry fruits. In a molecular docking study, perulactone demonstrated excellent binding affinity scores of −12.1 kcal/mol and −9.1 kcal/mol for caspase 7 and 3, respectively, whereas FDA-approved allosteric inhibitors (DICA and FICA) were found to show lower docking scores (−5.6 and −6.1 kcal/mol) against caspase 7 while (−5.0 and −5.1 kcal/mol) for caspase 3, respectively. MD simulations were used to validate the binding stability of perulactone in the active sites of caspase-7/-3, and the results showed outstanding stability with lower ligand RMSDs of 1.270–3.088 Å and 2.426–9.850 Å against the targeted receptor. Furthermore, we performed MMGBSA free binding energy, where the perulactone values of ΔGBind were determined to be −63.98 kcal/mol and −66.32 kcal/mol for both receptors (3IBF and 1NME), which are significantly better than the −45.16 kcal/mol and −39.51 kcal/mol for DICA as well as −26.37 kcal/mol and −15.50 kcal/mol for FICA, respectively. The drug resemblance of perulactone was effectively evaluated by ADMET. Thus, our findings indicated that perulactone could be an orally administered therapeutic candidate for regulating apoptosis in a variety of disorders. However, there may be an urgent need to study using in vitro and in vivo experiments. [ABSTRACT FROM AUTHOR]

This article thoroughly assesses the Chemical Looping Hydrogen Production (CLHP) process, aiming to enhance understanding of detailed dynamic simulations. It includes a concise historical overview of chemical looping technology, emphasizing recent commercial applications like combustion engines. The article discusses several cases of pilot and sub-pilot scale investigations, along with critical insights to identify the issues surrounding the commercialization of this technology. Furthermore, the review is extended to analyze several aspects of the process to develop a dynamic simulation model, including reactants, operating modes, kinetic parameters, and the process models. Key process materials such as reduction fuel, oxygen carriers and solid supports are carefully chosen to achieve target conversions and net-zero carbon emissions. The three-reactor system is meticulously defined, focusing on closed-loop production's thermodynamic and economic benefits. Detailed information is provided on reactions within each unit and the required operating regimes for continuous solid circulation. The review also examines mathematical modeling methods for dynamic simulation implementation to determine gas-solid profiles at pellet and reactor scales. Simulations derived from this study's concepts can be refined through parameter modification for optimal process operation and control system analysis for real-world industrial applications. Ultimately, this review contributes significantly to the commercialization of CLHP, offering an economically viable solution for sustainable hydrogen production. [Display omitted] • Chemical looping is an economically viable solution for producing hydrogen fuel. • Dynamic models can further the knowledge of chemical looping hydrogen production. • Mathematical simulations can quantify the acclaimed advantages of the process. • Quantified results can drive further investment towards process industrialization. [ABSTRACT FROM AUTHOR]

Recently, Egypt had seismic activity. These seismic events have affected the stability of minarets, especially historical ones. Weight is one of the minaret's main stability factors. The main objective of the current research is to perform a three-dimensional (3D) assessment of an existing minaret, determine its accurate spatial model, document its current condition, examine its stability in the event of earthquakes, and identify the requisite measures to safeguard the minaret from any potential damage. The masonry to construct the minaret was used by extracting and examining specimens of this substance to determine its physical characteristics. The current work created three-dimensional models of the Abou-Ghanam El-Bialy minaret using a terrestrial laser scanner (TLS) to document its current condition, as well as minaret was subjected to a free vibration analysis using 3D finite element modeling. Finally, the minaret's seismic behavior was assessed utilizing mode forms, base responses, and normal stresses. The surveying method effectively documented the Minarets' existing case. The 3D seismic analysis showed that the minaret responded dynamically to earthquake loading, with mode shapes, base reactions, and normal stresses being crucial characteristics. Based on these data, we may suggest procedures to protect the minaret during seismic events. [ABSTRACT FROM AUTHOR]

A wide range of bioactive compounds have been created using the versatile pharmacophore pyrimidine. In order to improve biological applications, we, therefore, envisioned adding these privileged moieties. In this work, we developed an efficient 2-aminopyrimidine derivatives. We further investigated the anticancer activity of all the compounds against colon cancer cell lines COLO-205 and HT-29. Out of several compounds synthesized, two compounds SD2 and SD4 have shown comparable potent anticancer activity when compared to standard Cabozantinib. The most potent cytotoxic compound against colon cancer cells in our study was found to be SD2 with an IC50 value of 9.57 μM. The investigation from molecular docking showed the best binding affinity. The complex stability within an enzyme’s pocket was demonstrated by the molecular dynamic simulation running for 100 ns. [ABSTRACT FROM AUTHOR]

In view of the current problems of slow crystallization rate, varying grain sizes, complex process conditions, and low safety in the preparation of CL−20/TNT cocrystal explosives in the laboratory, an opposite spray crystallization method is provided to quickly prepare ultrafine explosive cocrystal particles. CL−20/TNT cocrystal explosive was prepared using this method, and the obtained cocrystal samples were characterized by electron microscopy morphology, differential thermal analysis, infrared spectroscopy, and X-ray diffraction analysis. The effects of spray temperature, feed ratio, and preparation method on the formation of explosive cocrystal were studied, and the process conditions of the pneumatic atomization spray crystallization method were optimized. The crystal plane binding energy and molecular interaction forces between CL−20 and TNT were obtained through molecular dynamic simulation, and the optimal binding crystal plane and cocrystal mechanism were analyzed. The theoretical calculation temperature of the binding energy was preliminarily explored in relation to the preparation process temperature of cocrystal explosives. The mechanical sensitivity of ultrafine CL−20/TNT cocrystal samples was tested. The results showed that choosing acetone as the cosolvent, a spraying temperature of 30 °C, and a feeding ratio of 1:1 was beneficial for the formation and growth of cocrystal. The prepared CL−20/TNT cocrystal has a particle size of approximately 10 μm. The grain size is small, and the crystallization rate is fast. The impact and friction sensitivity of ultrafine CL−20/TNT cocrystal samples were significantly reduced. The experimental process conditions are simple and easy to control, and the safety of the preparation process is high, providing certain technical support for the preparation of high-quality cocrystal explosives. [ABSTRACT FROM AUTHOR]

The steelmaking–continuous casting process (SCCP) is a complex manufacturing process which exhibits the distinct features of process manufacturing. The SCCP involves a variety of production elements, such as multiple process routes, a wide array of smelting and auxiliary devices, and a variety of raw and auxiliary materials. The production-simulation of SCCP holds a natural advantage in being able to accurately depict the intricate production behavior involved, and this serves as a crucial tool for optimizing the production operation of the SCCP. This paper thoroughly considers the various production elements involved in the SCCP, such as the fluctuation of the converter smelting cycle, fluctuation of heat weight, and ladle operation. Based on the Plant Simulation software platform, a dynamic simulation model of the SCCP is established and detailed descriptions are provided regarding the design of an SCCP using dynamic-operation rules. Additionally, a dynamic operational control program for the SCCP is developed using the SimTalk language, one which ensures the continuous operation of the caster in the SCCP, using the discrete simulation platform. The effectiveness of the proposed dynamic simulation model is verified by the total completion time of the production plan, the transfer time of the heat among the different processes, and the frequency of ladle turnover. The simulation's results indicate that the dynamic simulation model has a satisfactory effect in simulating the actual production process. On this basis, the application effects of different schedules are compared and analyzed. Compared with a heuristic schedule, the optimized schedule based on the "furnace–machine coordinating" mode reduces the weighted value of total completion time by 8.7 min, reduces the weighted value of transfer waiting time by 45.5 min, and the number of rescheduling times is also reduced, demonstrating a better application effect and verifying the optimizing effect of the "furnace–machine coordinating" mode on the schedule. [ABSTRACT FROM AUTHOR]

Ceramic slurry is the raw material used in stereolithography, and its performance determines the printing quality. Rheological behavior, one of the most important physical factors in stereolithography, is critical in ceramic printing, significantly affecting the flow, spreading, and printing processes. The rheological behavior of SiO2 slurry used in stereolithography technology is investigated in the current research using different powder diameters and temperatures. The results present the apparent non-Newtonian behavior. The yielding characteristics occur in all cases. For single-powder cases, the viscosity decreases when the powder diameter is increased. When the nano-sized and micro-sized powders are mixed in different proportions, a more significant proportion of micron-sized powders will decrease the viscosity. With an increase in the nano-sized powders, the slurry exhibits the shear thinning behavior; otherwise, the shear thickening behavior is observed. Thus, the prediction model is built based on the use of the pelican optimization algorithm-deep extreme learning machine (POA-DELM), and the model in then compared with the fitted and traditional models to validate the effectiveness of the method. A more accurate viscosity prediction model will contribute to better fluid dynamic simulation in future work. [ABSTRACT FROM AUTHOR]

We present the results of molecular dynamics simulations of steady shear between a pair of neutral polymer brushes, as well as a pair of charged polymer brushes in the strongly compressed regime. The results of the molecular dynamic simulations of neutral and polyelectrolyte brushes in implicit solvent including normal forces, shear forces, viscosities and friction coefficients as a function of separation between brushes, are presented in the study. The comparison of the simulation results of neutral and charged brushes shows that the charged brushes is in the quasi-neutral regime, and the dependence of viscosity on the separation distance show the similar power law of neutral brushes. Our simulation results confirm that the implicit solvent simulations of polyelectrolyte brushes that ignore hydrodynamics interaction are in agreement with the scaling predictions qualitatively because of screening of hydrodynamic interaction and long-range electrostatic interactions on the correlation length scale. Both of neutral and charged brushes show the lubrication properties that the friction coefficient decreases with the separation decreases at enough large loads. However, a maximum of friction coefficients is observed for polyelectrolyte brushes, which is in contrast to the neutral brushes with monotonical dependence. [ABSTRACT FROM AUTHOR]

In order to explore the movement law of the feeding mechanism of 9YFLD-2.2 large square baler, through the analysis of the working process of feeding mechanism, the motion diagram of the large and small feeding fork were obtained, and the kinetic equation of two feeding forks have been established. The calculation of dynamic simulation for the two feeding forks were conducted with ADAMS, and the motion trajectory and velocity curve of the end point of the feeding forks have been obtained, which revealed the movement law of feeding mechanism. Dynamic simulation results show that the structure design for the feeding mechanism of 9YFLD-2.2 large square baler is reasonable, which can meet the feeding requirements of large square baler. [ABSTRACT FROM AUTHOR]

This study developed a dynamic simulation model of hydrogen refueling station (HRS) for the refueling process from high-pressure bank (HPB) to vehicle tank (VT) of fuel cell electric vehicle (FCEV). The model validation was confirmed by comparison with the results from the experimental test of Society of Automotive Engineers (SAE) J2601 protocol. After the validation, the same components and their specifications are used for the analysis of the refueling characteristics in various initial and boundary conditions by a commercial process simulator (Aspen HYSYS). The pressure and temperature profiles of the VT and external temperature conditions were defined for the analysis of the hydrogen refueling characteristics. The dynamic simulation model was in a good agreement with the experimental data and supports to evaluate hydrogen refueling efficiency by the analysis of refueling characteristics. [ABSTRACT FROM AUTHOR]

Peridynamics describes the material in a non-local form and is very suited for the simulation of dynamic fracture. However, one significant effect regarding dynamic fracture is the correct handling of elastic deformation, like the pressure and tension waves inside a body, due to dynamic boundary conditions like an impact or impulse. Many peridynamic material formulations have been developed with differences in this regard. This study investigates the elastic wave propagation characteristics of bond-based, ordinary state-based, continuum kinematics-inspired peridynamics and a local continuum consistent correspondence formulation. Multiple parameters of a longitudinal pressure wave inside an elastic bar are studied. While all formulations demonstrate adequate wave propagation handling, all except the correspondence formulation are sensitive to incomplete horizons. The local continuum consistent formulation does not suffer from the surface effect and models the wave propagation with perfect accuracy. [ABSTRACT FROM AUTHOR]

Unveiling the dynamic active site of defective carbon-based electrocatalysts for hydrogen peroxide production. [Display omitted] Defective carbon materials have emerged as promising candidates for the electrocatalysis of oxygen reduction reaction (ORR) to selectively produce H 2 O 2. However, distinguishing the roles of oxygenates and carbon defects in carbon for 2e- ORR remains to be challenging. In a recent issue of Nature Communications, Yao and coworkers pinpointed the major active sites in oxygenated carbon materials and identified the key intermediate employing a series of dynamic and simulation techniques. In addition to highlight the proposed work, this comment article also discussed pioneering methodologies to characterize structure dynamics and probe the integral active center for rational design of carbon based catalysts with atomic precision. [ABSTRACT FROM AUTHOR]

Carbon nanotube (CNT) is a material with high modulus, high tensile strength, good flexibility and large specific surface area. This material has become very popular and has been also applied as an asphalt modifier. In the current research, multi-walled carbon nanotubes (MWCNTs) and styrene-butadiene-styrene (SBS) were employed as modifiers to fabricate MWCNTs/SBS composite-modified asphalt binder (hereinafter referred to as MCSA). The technical performance of MCSA was evaluated by performance tests and the optimal content of MWCNTs was determined. MCSA dispersion characteristics and interactions of components were investigated by microscopic test methods. Interactions of molecules and tensile behavior of MWCNTs in MCSA were explored by molecular dynamics (MD) simulation. The modification mechanism of MWCNTs was studied at the macro, micro and molecular levels. The following conclusions were drawn: According to macroscopic test results, the optimal content range of MWCNTs was 0.4% to 0.6%. MWCNTs modification process on asphalt binder was a physical modification. MWCNTs enhanced interactions among components and this effect was most obvious when MWCNTs content was 0.6%. The results of the macroscopic test were verified by the microscopic test. MWCNTs molecules could couple with SBS modifier as well as asphalt component molecules, thereby enhancing the interaction of each component in the system. MWCNTs mainly enhanced molecular interactions by increasing van der Waals energy in MCSA system, to make it more stable. MWCNTs do not break during the pull-out process. The molecules of asphalt component, SBS modifier and MWCNTs penetrated each other, which enhanced system stability to resist external loads and improved the mechanical properties of MCSA. [ABSTRACT FROM AUTHOR]

The building industry requires the development of a ductile lateral force resisting system made of mass timber to help mass timber to continue to grow in popularity as the primary structural building material. The OpenSees framework was used to develop a numerical model of a single-story timber frame with a timber buckling-restrained brace, which was validated by the results of a previously completed series of quasistatic cyclic timber buckling-restrained brace (TBRB) component and subassembly tests. The experimental validation included a model developed for the hysteretic behavior of the TBRB and the rotational capacity of beam–column joints made with mass ply lam (MPL) panels, two slotted-in steel plates, and a number of steel dowels. The single-story model TBRB braced frame was then expanded to a numerical model of an eight-story mass timber buckling-restrained braced frame. The TBRB frame was analyzed with static pushover, quasistatic cyclic loads, and earthquake simulations. During the simulation of eleven design-level earthquake ground motions, the building experienced a peak interstory drift at of 2.54% at the first-floor level and a peak floor acceleration of 1.7g at the roof. The numerical model developed in this research of a timber buckling-restrained braced frame with TBRBs is novel and could be used to design timber buckling-restrained braced frames as a ductile lateral force resisting solution for mass timber buildings in seismic regions. [ABSTRACT FROM AUTHOR]

[Display omitted] Hypothesis : Understanding the rules that control the assembly of nanostructured soft materials at interfaces is central to many applications. We hypothesize that electrolytes can be used to alter the hydration shell of amphiphilic oligomers at the air-aqueous interface of Langmuir films, thereby providing a means to control the formation of emergent nanostructures. Experiments : Three representative salts – (NaF, NaCl, NaSCN) were studied for mediating the self-assembly of oligodimethylsiloxane methylimidazolium (ODMS-MIM+) amphiphiles in Langmuir films. The effects of the different salts on the nanostructure assembly of these films were probed using vibrational sum frequency generation (SFG) spectroscopy and Langmuir trough techniques. Experimental data were supported by atomistic molecular dynamic simulations. Findings : Langmuir trough surface pressure – area isotherms suggested a surprising effect on oligomer assembly, whereby the presence of anions affects the stability of the interfacial layer irrespective of their surface propensities. In contrast, SFG results implied a strong anion effect that parallels the surface activity of anions. These seemingly contradictory trends are explained by anion driven tail dehydration resulting in increasingly heterogeneous systems with entangled ODMS tails and appreciable anion penetration into the complex interfacial layer comprised of headgroups, tails, and interfacial water molecules. These findings provide physical and chemical insight for tuning a wide range of interfacial assemblies. [ABSTRACT FROM AUTHOR]

The dynamic carbon footprint profile of methanol production from steel mill gases is affected by fluctuations of steel mill gas flow rates and compositions, as well as the composition of electricity mix. The cross‐industrial network of steel mill, gas conditioning, hydrogen production, chemical synthesis, and power generation was simulated under dynamic conditions. Dynamic life cycle assessment (LCA) was carried out for computing the dynamic carbon footprint profile in 15‐min resolution for the integrated system of steel and methanol production. The dynamic LCA indicated that the CO2 emissions in a power plant, electrolytic hydrogen demand, and variations in electricity mix were the major drivers of the fluctuations in the total carbon footprint. Dynamic LCA is useful for quantifying temporal uncertainty in environmental impacts. This insight can be used to analyze uncertainty in impacts for downstream products, processes, and use cases. [ABSTRACT FROM AUTHOR]

A control strategy must be developed to maintain the product composition of the two- or more-mixed-flow reactor series. In this research, a two-mixing tank series (TMTS) was utilized in the laboratory to approach the two-mixed flow reactors' problems. Both tanks are designed to overflow so that the volume remains constant. The salt solution was directly fed to Tank 1, while the water was charged to both tanks as the mixing progressed. The output of Tank-1 flowed to Tank-2 through a rather long pipe, resulting in dead time in Tank-2. The Smith predictor was applied to overcome dead time. The PRC (process reaction curve) method was used to tune the PID (proportional-integral-derivative) parameters of Tank-1 and Tank-2. The novel composition controls, adaptive-PID (APID) and modified metaheuristic adaptive-PID (MMAPID), have been proposed and compared with conventional PID. The mathematical models were rigorously examined through XCOS simulations. The processing system is considered sensitive to changes in input disturbances since the process time constants of both tanks were quite low. The dead time of 0.5 minutes was found in Tank 2. The PID parameters produced by PRC experiments resulted in stable responses to changes in the disturbance system. As shown in the dynamic simulation study, both novel APID and MMAPID give almost the same results; their responses are faster than the conventional PID. Based on the integral absolute error (IAE) results, APID with scheduling PID parameters produced the smallest IAE and outperformed the conventional PID. The results of the study highlight APID and MMAPID potential in PID control applications for composition control in a TMTS. The combined APID-Smith and MMAPID-Smith were able to overcome the dead time well. This study creates opportunities for engineers and professionals to use cutting-edge control technologies, improving automation and chemical process industries. [ABSTRACT FROM AUTHOR]

Seismological studies have exposed numerous ultralow velocity zones (ULVZs) exhibiting extraordinary physical attributes at Earth's core-mantle boundary, yet their compositions and origins remain controversial. Water-iron reaction can generate unique phases under lowermost-mantle conditions and likely plays a crucial role in forming ULVZs. Through first-principles molecular dynamic simulations with machine learning techniques, we determine that iron hydride, the product of water-iron reaction, is stable as a superionic phase at the core-mantle boundary. This superionic iron hydride has much slower velocities and a higher density than the ambient mantle under lowermost-mantle conditions. Accumulation of iron hydride, created through either a chemical reaction between subducted water and iron or solidification of core material entrained in the lower mantle by convection, can explain the seismic observations of ULVZs particularly those associated with subduction. This work suggests that water may have a substantial role in creating seismic heterogeneities at the core-mantle boundary. [ABSTRACT FROM AUTHOR]

AbstractMicrobes have been extensively utilized for their sustainable and scalable properties in synthesizing desired bio-products. However, insufficient knowledge about intracellular metabolism has impeded further microbial applications. The genome-scale metabolic models (GEMs) play a pivotal role in facilitating a global understanding of cellular metabolic mechanisms. These models enable rational modification by exploring metabolic pathways and predicting potential targets in microorganisms, enabling precise cell regulation without experimental costs. Nonetheless, simplified GEM only considers genome information and network stoichiometry while neglecting other important bio-information, such as enzyme functions, thermodynamic properties, and kinetic parameters. Consequently, uncertainties persist particularly when predicting microbial behaviors in complex and fluctuant systems. The advent of the omics era with its massive quantification of genes, proteins, and metabolites under various conditions has led to the flourishing of multi-constrained models and updated algorithms with improved predicting power and broadened dimension. Meanwhile, machine learning (ML) has demonstrated exceptional analytical and predictive capacities when applied to training sets of biological big data. Incorporating the discriminant strength of ML with GEM facilitates mechanistic modeling efficiency and improves predictive accuracy. This paper provides an overview of research innovations in the GEM, including multi-constrained modeling, analytical approaches, and the latest applications of ML, which may contribute comprehensive knowledge toward genetic refinement, strain development, and yield enhancement for a broad range of biomolecules. [ABSTRACT FROM AUTHOR]

Enhancing the understanding of hydroxide transport mechanisms in anion exchange membranes (AEMs) is beneficial for the rational design of high‐performance AEMs in the renewable energy system. However, the high complexity and lack of adequate analytic tools make it challenging to clarify different mechanisms unambiguously. Herein, we developed an in‐house toolkit, the Reactive Diffusion Analyzer (RDAnalyzer), to conduct an effective analysis of hydroxide diffusion mechanisms from ReaxFF molecular dynamic simulations. Using the experimentally well‐synthesized T20NC6NC5N as a model system, we successfully decoupled the hydroxide diffusion mechanisms into free Vehicular and free Grotthuss, as well as associated Vehicular and associated Grotthuss, which was not yet achieved previously. Meanwhile, RDAnalyzer managed to specifically identify the drift length of hydroxide species for each mechanism under the electric field, which worked as a useful variable for calculating the conductivity of AEMs. Our theoretically predicted conductivity for T20NC6NC5N agrees reasonably with experimental results, indicating the reliability of RDAnalyzer. This work not only provides a rational understanding of the complex hydroxide diffusion mechanisms in AEMs but also holds the potential to guide the rational design of high‐performance AEMs with computations. [ABSTRACT FROM AUTHOR]

Enhancing the understanding of hydroxide transport mechanisms in anion exchange membranes (AEMs) is beneficial for the rational design of high‐performance AEMs in the renewable energy system. However, the high complexity and lack of adequate analytic tools make it challenging to clarify different mechanisms unambiguously. Herein, we developed an in‐house toolkit, the Reactive Diffusion Analyzer (RDAnalyzer), to conduct an effective analysis of hydroxide diffusion mechanisms from ReaxFF molecular dynamic simulations. Using the experimentally well‐synthesized T20NC6NC5N as a model system, we successfully decoupled the hydroxide diffusion mechanisms into free Vehicular and free Grotthuss, as well as associated Vehicular and associated Grotthuss, which was not yet achieved previously. Meanwhile, RDAnalyzer managed to specifically identify the drift length of hydroxide species for each mechanism under the electric field, which worked as a useful variable for calculating the conductivity of AEMs. Our theoretically predicted conductivity for T20NC6NC5N agrees reasonably with experimental results, indicating the reliability of RDAnalyzer. This work not only provides a rational understanding of the complex hydroxide diffusion mechanisms in AEMs but also holds the potential to guide the rational design of high‐performance AEMs with computations. [ABSTRACT FROM AUTHOR]

The efficient production and sustainable operation of water electrolysis hydrogen production equipment within renewable energy systems, characterized by intermittency and volatility, necessitates dynamic simulation for the development of optimized control systems. This paper proposes the application and modification of a data-driven deep-learning model to simultaneously simulate the thermal and electrochemical responses of an alkaline water electrolyzer (AWE), yielding exceptional performance and versatility. By utilizing 4840 h of comprehensive experimental data, the causal relationships among electrolyzer operating parameters are resolved, classifying them into set values and response values for the proposed dynamic model. The model architecture is based on an attention mechanism and designed with hybrid input. Notable enhancements include embedding flow-leveraged polarization function, creating set-value cross-attention, and adopting probability-sparse attention, all of which are validated through both the validation and simulation results. Extensive exploration of various structural and training parameters leads to the selection of the best-performing model. When applied to simulation across all experimental data, the median mean percentage absolute error of the optimal model in cell voltage is a mere 1.3%, while the error in temperature is only 3.5%. Moreover, under typical operating conditions, the simulation error for both voltage and temperature remain below 2%, highlighting the outstanding dynamic modeling and simulation capabilities. These results demonstrate the potential of the proposed model for future hydrogen energy applications in dynamic control and operational optimization within renewable energy system for higher performance and better conversion efficiency. • Deep-learning model for dynamic thermoelectric simulation of water electrolyzers. • Flow-leveraged polarization function and set-value cross-attention mechanism. • Excellent accuracy, thermoelectric error of 3.5% and 1.3%, respectively. • Insights for optimizing control strategies of electrolyzer for higher efficiency. [ABSTRACT FROM AUTHOR]

By addressing the phenomenon of carbody abnormal vibrations in the field, the acceleration of the carbody and bogie was measured using accelerometers, and the diamond mode of the carbody was identified. The equivalent conicity of the wheelset and the acceleration at the frame end indicated that the shaking of the carbody was caused by bogie hunting. In the SIMPACK simulation, the acceleration frequency and amplitude at the frame end and midsection of the side beam were calculated. The lateral deformation amplitude of the side beam in the finite element model was extracted, and a modal shape function for the diamond-shaped mode was established. By utilizing the modal vibration equation, the modal generalized forces of the carbody were computed, revealing that, during carbody shaking, the yaw damper force contributed significantly among the forces of the secondary suspension, with the phase difference between the front and rear bogies approaching 180°. This insight offers a novel perspective for subsequent active control strategies. Subsequently, these modal generalized forces were applied as external excitation to a coupled vibration model encompassing both the carbody and transformer. Aiming to reduce the acceleration amplitude at the side beam, the transformer was treated as a dynamic vibration absorber, allowing for the optimization of its lateral suspension parameters. As a result, the lateral and vertical acceleration amplitudes at the side beam were concurrently reduced, with the maximum decrease reaching 58.5%, significantly enhancing the ride comfort. [ABSTRACT FROM AUTHOR]

Introduction: Muscles play a critical role in supporting joints during activities of daily living, owing, in part, to the phenomenon of short-range stiffness. Briefly, when an active muscle is lengthened, bound cross-bridges are stretched, yielding forces greater than what is predicted from the force length relationship. For this reason, short-range stiffness has been proposed as an attractive mechanism for providing joint stability. However, there has yet to be a forward dynamic simulation employing a cross-bridge model, that demonstrates this stabilizing role. Therefore, the purpose of this investigation was to test whether Huxley-type muscle elements, which exhibit short-range stiffness, can stabilize a joint while at constant activation. Methods: We analyzed the stability of an inverted pendulum (moment of inertia: 2.7 kg m2) supported by Huxley-type muscle models that reproduce the short-range stiffness phenomenon. We calculated the muscle forces that would provide sufficient short-range stiffness to stabilize the system based in minimizing the potential energy. Simulations consisted of a 50 ms long, 5 Nm square-wave perturbation, with numerical simulations carried out in ArtiSynth. Results: Despite the initial analysis predicting shared activity of antagonist and agonist muscles to maintain stable equilibrium, the inverted pendulum model was not stable, and did not maintain an upright posture even with fully activated muscles. Discussion & conclusion: Our simulations suggested that short-range stiffness cannot be solely responsible for joint stability, even for modest perturbations. We argue that short-range stiffness cannot achieve stability because its dynamics do not behave like a typical spring. Instead, an alternative conceptual model for short-range stiffness is that of a Maxwell element (spring and damper in series), which can be obtained as a first-order approximation to the Huxley model. We postulate that the damping that results from short-range stiffness slows down the mechanical response and allows the central nervous system time to react and stabilize the joint. We speculate that other mechanisms, like reflexes or residual force enhancement/depression, may also play a role in joint stability. Joint stability is due to a combination of factors, and further research is needed to fully understand this complex system. [ABSTRACT FROM AUTHOR]

3,4-bis(3-nitrofurazan-4-yl) furoxan (DNTF) is an explosive with excellent performance, and the use of DNTF as a high-energy component is of great significance for improving the comprehensive performance of weapons. To explore the effect of DNTF on low-melting-point molten carrier explosives, the compatibility between DNTF and other low-melting-point explosives was analyzed by differential scanning calorimetry, and mechanical sensitivity was tested. The compatibility and cohesive energy density between DNTF and other low-melting-point explosives were calculated by Materials Studio. The results showed that DNTF has good compatibility with most low-melting-point explosives, and the peak temperature change of the mixed system formed by melt-casting is not obvious. Among them, DNTF has the best compatibility with MTNP, TNT, and DNAN; moderate compatibility with DFTNAN and DNP; and the worst compatibility with DNMT. The sensitivity test results indicate that the combination of DNTF and TNT has the most significant reduction in mechanical sensitivity. DFTNAN and MTNP have better stability than DNTF and can generate strong interaction forces with DNTF. Other low-melting-point explosives mixed with DNTF have lower intermolecular forces than DNTF. The DNTF/MTNP system requires the most energy to phase change when heated compared to other mixed systems and is the least sensitive to heat. The DNTF/DNMT system has the lowest cohesive energy density and is the most sensitive to heat. [ABSTRACT FROM AUTHOR]

This work focuses on the well-known issue of mass conservation in the context of the finite element technique for computational fluid dynamic simulations. Specifically, non-conventional finite element families for solving Navier–Stokes equations are investigated to address the mathematical constraint of incompressible flows. Raviart–Thomas finite elements are employed for the achievement of a discrete free-divergence velocity. In particular, the proposed algorithm projects the velocity field into the discrete free-divergence space by using the lowest-order Raviart–Thomas element. This decomposition is applied in the context of the projection method, a numerical algorithm employed for solving Navier–Stokes equations. Numerical examples validate the approach's effectiveness, considering different types of computational grids. Additionally, the presented paper considers an interface advection problem using marker approximation in the context of multiphase flow simulations. Numerical tests, equipped with an analytical velocity field for the surface advection, are presented to compare exact and non-exact divergence-free velocity interpolation. [ABSTRACT FROM AUTHOR]

Point clouds captured using laser scanners mounted on mobile platforms contain errors at the centimetre to decimetre level due to motion distortion. In applications such as lidar odometry or SLAM, this motion distortion is often ignored. However, in applications such as HD mapping or precise vehicle localisation, it is necessary to correct the effect of motion distortion or ‘deskew’ the point clouds before using them. Existing methods for deskewing point clouds mostly rely on high frequency IMU, which may not always be available. In this paper, we propose a straightforward approach that uses the registration of consecutive point clouds to estimate the motion of the scanner and deskew the point clouds. We introduce a novel surface‐based evaluation method to evaluate the performance of the proposed deskewing method. Furthermore, we develop a lidar simulator using the reverse of the proposed deskewing method which can produce synthetic point clouds with realistic motion distortion. [ABSTRACT FROM AUTHOR]

The practical application of traditional data‐driven techniques for process monitoring encounters significant challenges due to the inherent nonlinear and dynamic nature of most industrial processes. Aiming at the problem of nonlinear dynamic process monitoring, a novel fault detection method based on dynamic kernel principal component analysis combined with weighted structural difference (DKPCA‐WSD) is proposed in this paper. Initially, the proposed method leverages a sophisticated nonlinear transformation to project the augmented matrix of the original input data into a high‐dimensional feature space, thereby facilitating the establishment of a DKPCA model. Subsequently, the WSD statistic is computed, utilizing a widely known sliding window technique, to quantify the mean and standard deviation differences across data structures. Ultimately, the WSD statistic is utilized for fault detection, completing the process monitoring task. By integrating the capability of DKPCA to capture nonlinear dynamic characteristics with the effectiveness of the WSD statistic in mitigating the impact of non‐Gaussian data distributions, DKPCA‐WSD significantly enhances the monitoring performance of traditional DKPCA in nonlinear dynamic processes. The proposed method is evaluated through a numerical case exhibiting nonlinear dynamic behaviors and a simulation model of a continuous stirred tank reactor. A comparative analysis with conventional methods, including principal component analysis (PCA), dynamic principal component analysis, KPCA, PCA similarity factor (SPCA), DKPCA, and moving window KPCA (MWKPCA), demonstrates that DKPCA‐WSD outperforms traditional fault detection techniques in nonlinear dynamic processes, offering a substantial improvement in monitoring performance. [ABSTRACT FROM AUTHOR]

Cells store triacylglycerol (TAG) within lipid droplets (LDs). A dynamic model describing complete LD formation at the endoplasmic reticulum (ER) membrane does not yet exist. A biochemical‐biophysical model of LD synthesis is proposed. It describes the time‐dependent accumulation of TAG in the ER membrane as the formation of a potential LD (pLD) bounded by spherical caps of the inner and outer monolayers of the membrane. The expansion rate of the pLD depends on the TAG supply, the elastic properties of the ER membrane, and the recruitment of phospholipids (PLs) to the cap‐covering monolayers. Model simulations provided the following insights: (a) Marginal differences in the surface tension of the cap monolayers are sufficient to fully drive the expansion of the pLD towards the cytosol or lumen. (b) Selective reduction of PL supply to the luminal monolayer ensures stable formation of cytosolic LDs, irrespective of variations in the elasto‐mechanical properties of the ER membrane. (c) The rate of TAG supply to the cytosolic monolayer has a major effect on the size and maturation time of LDs but has no significant effect on the TAG export per individual LD. The recruitment of additional PLs to the cap monolayers of pLDs critically controls the budding direction, size, and maturation time of LDs. The ability of cells to acquire additional LD initiation sites appears to be key to coping with acutely high levels of potentially toxic free fatty acids. [ABSTRACT FROM AUTHOR]

This paper presents a novel adaptation of the conventional approximate Bayesian computation sequential Monte Carlo (ABC-SMC) sampling algorithm for parameter estimation in the presence of uncertainties, coined combinatorial ABC-SMC. Inference of this type is used in situations where there does not exist a closed form of the associated likelihood function, which is replaced by a simulating model capable of producing artificial data. In the literature, conventional ABC-SMC is utilised to perform inference on continuous parameters. The novel scheme presented here has been developed to perform inference on parameters that are high-dimensional binary, rather than continuous. By altering the form of the proposal distribution from which to sample candidates in subsequent iterations (referred to as waves), high-dimensional binary variables may be targeted and inferred by the scheme. The efficacy of the proposed scheme is demonstrated through application to vibration data obtained in a structural dynamics experiment on a fibre-optic sensor simulated as a finite plate with uncertain boundary conditions at its edges. Results indicate that the method provides sound inference on the plate boundary conditions, which is validated through subsequent application of the method to multiple vibration datasets. Comparisons between appropriate forms of the metric function used in the scheme are also developed to highlight the effect of this element in the schemes convergence. [ABSTRACT FROM AUTHOR]

For conformal contact situations, some of the assumptions employed in classical contact theories, such as the flatness of the contact area, lose their validity. Existing conformal contact models are challenged by either accuracy or computational efficiency. With the aim of achieving a balanced trade-off between these contrasting requirements, this paper proposes a new simplified method to solve conformal rolling contact problems, which is based on fast non-Hertzian contact model INFCON and FaStrip. Numerical experiments are performed for two typical wheel/rail conformal contact scenarios to assess the performance of the proposed method, taking as the reference the CONTACT method for conformal contacts. The comparative analyses show that the proposed method is in good agreement with the reference method in terms of the determination of the contact stresses, total forces, and the prediction of wear, whereas the traditional half-space approach fails to capture the main features of the conformal contacts. In addition, the high computational efficiency of the proposed method shows the potential for application in vehicle dynamic simulation and damage analysis. [ABSTRACT FROM AUTHOR]

A methodology is presented for downscaling the Euro‐CORDEX climatic projections in order to derive spatially and temporally correlated weather fields that can be used for risk and resilience assessment of large‐scale asset portfolios or interconnected infrastructure. The temporal resolution of the Euro‐CORDEX data is downscaled to a 10 min basis by employing a modified analogue‐type approach that utilizes the k‐NN algorithm along with measurements from weather stations. The aim is to generate composite "Frankenstein" days comprising 144 jigsaw pieces of observed 10 min timeseries that are scaled and/or shifted, and matched together to form a continuous daily record. These point‐estimates, valid only at the locations of the weather stations, are expanded spatially by employing high‐fidelity weather intensity measure fields that provide variable yet synchronous patterns of weather parameters at all locations of interest. As a case study, the Euro‐CORDEX projections for wind, temperature, and precipitation are downscaled for the Metsovo‐Panagia segment of Egnatia Odos highway in Greece, by employing high‐fidelity Computational Fluid Dynamic simulations that account for the topography of the site to simulate turbulent wind flows. These are combined with measurements of two local weather stations to generate the Frankenstein timeseries and corresponding weather fields that can be used for estimating operability, recovery and direct/indirect loss statistics on an event‐by‐event basis for an ensemble of interconnected highway assets. [ABSTRACT FROM AUTHOR]

Living organisms are constructed from proteins that assemble into biomolecular complexes, each with a unique shape and function. Our knowledge about the structure–activity relationship of these complexes is still limited, mainly because of their small size, complex structure, fast processes, and changing environment. Furthermore, the constraints of current microscopic tools and the difficulty in applying molecular dynamic simulations to capture the dynamic response of biomolecular complexes and long-term phenomena call for new supplementary tools and approaches that can help bridge this gap. In this paper, we present an approach to comparing biomolecular and origami hierarchical structures and apply it to comparing bacterial microcompartments (BMCs) with spiral-based origami models. Our first analysis compares proteins that assemble the BMC with an origami model called "flasher", which is the unit cell of an assembled origami model. Then, the BMC structure is compared with the assembled origami model and based on the similarity, a physical scaled-up origami model, which is analogous to the BMC, is constructed. The origami model is translated into a computer-aided design model and manufactured via 3D-printing technology. Finite element analysis and physical experiments of the origami model and 3D-printed parts reveal trends in the mechanical response of the icosahedron, which is constructed from tiled-chiral elements. The chiral elements rotate as the icosahedron expands and we deduce that it allows the BMC to open gates for transmembrane passage of materials. [ABSTRACT FROM AUTHOR]

Mathematical modeling of bearing faults, worn tool holder taper contact interface, and unbalance are presented and integrated into a digital dynamic model of spindles in Part I of this paper. These faults lead to changes in preload and dynamic stiffness over time, consequently resulting in observable vibrations. This paper predicts the vibrations of a spindle at a particular measurement location by simulating the presence of a specific fault or multiple faults during spindle rotation. The vibration spectra generated by the digital spindle model at the spindle speed and its harmonics, the changes in the natural frequencies, and dynamic stiffnesses are correlated to faults with experimental validations. The simulated vibration spectrums are later used in training an artificial neural network for fault condition monitoring presented in Part III of the paper. [ABSTRACT FROM AUTHOR]

InhA is an enoyl acyl carrier reductase that catalyzes the chemo-selective reduction of its 2-trans-enoyl-ACP substrate. The pharmacological effects of the frontline medications used in the treatment of tuberculosis are elicited by inhibiting the enzyme InhA, which disrupts the mycolic acid biosynthesis pathway. The present study involves development of ligand-based pharmacophore model, docking studies, generation of 3D-QSAR model, and molecular dynamic simulation studies of virtually screened putative InhA inhibitors. The best field-based 3D-QSAR model was validated using partial least-square regression (PLS) method with high regression coefficient for training set (R2) = 0.9256 and test set (R2) = 0.7542, cross-validated coefficient (rcv2) = 0.72 and R2pred = 0.9764. Also, virtual screening yielded compounds 4, 25, 1, and 30 exhibiting appreciable interactions (docking scores −5.972, −3.819, −3.801, and −3.701, respectively with InhA synthetase; PDB ID: 1BVR). Further, ADMET studies supported drug-like potential of compounds 25, 1, and 30 whereas compound 4 showed negligible human oral absorption. The molecular dynamic simulation studies of the top scored molecule 25 suggested stability of 25-1BVR complex over the course of simulation run. Therefore, this work can be helpful for future discovery of novel InhA inhibitors against drug-resistant tuberculosis. [ABSTRACT FROM AUTHOR]

This manuscript presents a new report on the in vitro antimicrobial photo-inactivation of foodborne microorganisms (Salmonella spp. and Listeria monocytogenes) using tetra-cationic porphyrins. Isomeric tetra-cationic porphyrins (3MeTPyP, 4MeTPyP, 3PtTPyP, and 4PtTPyP) were tested, and antimicrobial activity assays were performed at specific photosensitizer concentrations under dark and white-light LED irradiation conditions. Among the tested bacterial strains, 4MeTPyP exhibited the highest efficiency, inhibiting bacterial growth within just 60 min at low concentrations (17.5 μM). The minimal inhibitory concentration of 4MeTPyP increased when reactive oxygen species scavengers were present, indicating the significant involvement of singlet oxygen species in the photooxidation mechanism. Furthermore, the checkerboard assay testing the association of 4MeTPyP showed an indifferent effect. Atomic force microscopy analyses and dynamic simulations were conducted to enhance our understanding of the interaction between this porphyrin and the strain's membrane. [ABSTRACT FROM AUTHOR]

Several computational methods have been developed to identify neutralizing antibodies (NAbs) covering four dengue virus serotypes (DENV-1 to DENV-4); however, limitations of the dataset and the resulting performance remain. Here, we developed a new computational framework to predict potent and stable NAbs against DENV-1 to DENV-4 using only antibody (CDR-H3) and epitope sequences as input. Specifically, our proposed computational framework employed sequence-based ML and molecular dynamic simulation (MD) methods to achieve more accurate identification. First, we built a novel dataset (n = 1108) by compiling the interactions of CDR-H3 and epitope sequences with the half maximum inhibitory concentration (IC50) values, which represent neutralizing activities. Second, we achieved an accurately predictive ML model that showed high AUC values of 0.879 and 0.885 by tenfold cross-validation and independent tests, respectively. Finally, our computational framework could be applied to filter approximately 2.5 million unseen antibodies into two final candidates that showed strong and stable binding to all four serotypes. In addition, the most potent and stable candidate (1B3B9_V21) was evaluated for its development potential as a therapeutic agent by molecular docking and MD simulations. This study provides an antibody computational approach to facilitate the high-throughput identification of NAbs and accelerate the development of therapeutic antibodies. [ABSTRACT FROM AUTHOR]

The dynamic control of an active magnetic bearing (AMB) rotor after the rotor falls to its touch-down bearings has always been a difficult problem for applications such as flywheel energy storage. The rotor drop process has obvious nonlinear dynamic characteristics. This paper first discusses the structure of AMBs and the basic principles of their control. Starting from the electromagnetic forces that electromagnets can provide, the problem is simplified to the influence of an electromagnetic force with constant damping characteristics on the dynamic characteristics of a dropped rotor. A dynamic model of an AMB rotor with touch-down bearings was built and the contact force model between the rotor and the touch-down bearings was determined. A constant damping electromagnetic force was applied in two ways to verify the dynamic control feasibility of a dropped rotor through magnetic bearings. The simulation results show that the dropped rotor recovery control is feasible by applying a reasonable electromagnetic force. [ABSTRACT FROM AUTHOR]

Crushing is a critical operation in mineral processing, and its efficient performance is vital for minimizing energy consumption, maximizing productivity, and maintaining product quality. However, due to variations in feed material characteristics and safety constraints, achieving the intended circuit performance can be challenging. In this study, a centralized control strategy based on a finite state machine (FSM) is developed to improve the operations of an iron ore crushing circuit. The aim is to increase productivity by manipulating the closed-side-setting (CSS) of cone crushers and the speed of an apron feeder while considering intermediate storage silo levels and cone crusher power limits, as well as product quality. A dynamic simulation was conducted to compare the proposed control strategy with the usual practice of setting CSS to a constant value. Four scenarios were analyzed based on variations in bond work index (BWI) and particle size distribution. The simulation results demonstrate that the proposed control strategy increased average productivity by 6.88% and 48.77% when compared to the operation with a constant CSS of 38 mm and 41 mm, respectively. The proposed strategy resulted in smoother oscillation without interlocking, and it maintained constant flow rates. This ultimately improved circuit reliability and predictability, leading to reduced maintenance costs. [ABSTRACT FROM AUTHOR]

BACKGROUND RESULTS CONCLUSION Mycotoxin contamination of food has been gaining increasing attention. Hidden mycotoxins that interact with biological macromolecules in food could make the detection of mycotoxins less accurate, potentially leading to the underestimation of the total exposure risk. Interactions of the mycotoxins alternariol (AOH) and alternariol monomethyl ether (AME) with high‐molecular glutenin were explored in this study.The recovery rates of AOH and AME (1, 2, and 10 μg kg−1) in three types of grains (rice, corn, and wheat) were relatively low. Molecular dynamics (MD) simulations indicated that AOH and AME bound to glutenin spontaneously. Hydrogen bonds and π‐π stacking were the primary interaction forces at the binding sites. Alternariol with one additional hydroxyl group exhibited stronger binding affinity to glutenin than AME when analyzing average local ionization energy. The average interaction energy between AOH and glutenin was −80.68 KJ mol−1, whereas that of AME was −67.11 KJ mol−1.This study revealed the mechanisms of the interactions between AOH (or AME) and high‐molecular glutenin using MD and molecular docking. This could be useful in the development of effective methods to detect pollution levels. These results could also play an important role in the evaluation of the toxicological properties of bound altertoxins. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

One of the most challenging issues scientists face is finding a suitable non-invasive treatment for cancer, as it is widespread around the world. The efficacy of phytochemicals that target oncogenic pathways appears to be quite promising and has gained attention over the past few years. We investigated the effect of docking phytochemicals isolated from the rhizomes of the Cimicifuga foetida plant on different domains of the IκB kinase alpha (IKK1/alpha) protein. The Cimicifugoside H-2 phytochemical registered a high docking score on the activation loop of IKK1/alpha amongst the other phytochemicals compared to the positive control. The interaction of the protein with Cimicifugoside H-2 was mostly stabilized by hydrogen bonds and hydrophobic interactions. A dynamic simulation was then performed with the Cimicifugoside H-2 phytochemical on the activation loop of IKK1/alpha, revealing that Cimicifugoside H-2 is a possible inhibitor of this protein. The pharmacokinetic properties of the drug were also examined to assess the safety of administering the drug. Therefore, in this in silico study, we discovered that the Cimicifugoside H-2 phytochemical inhibits the actively mutated conformation of IKK1/alpha, potentially suppressing the nuclear factor kappa light chain enhancer of activated B cells (NF-κB) pathway. [ABSTRACT FROM AUTHOR]

Aiming at the difficulty of dynamic modeling of a hybrid robotic arm, a dynamic model system of industrial robotic arm based on Simscape Multibody was established with the MG400 robotic arm as the research object, which combines the motion control and data acquisition modules. The model is dynamically visualized and provides a convenient platform for studying the control algorithm of the robot arm. In response to the issues of sluggish speed and substantial position error in robot trajectory tracking control of a traditional controller, a variable gain iterative learning control methodology was designed. The robot arm control system model was employed to corroborate the trajectory tracking control under the stipulated target trajectory. The empirical outcomes indicate that in comparison to the traditional controller and the fixed-gain iterative learning controller, the variable-gain iterative learning controller can regulate the robot end trajectory more precisely, with swift tracking speed and accurate tracking posture, demonstrating commendable feasibility and portability. It offers an open-source research and development platform for the dynamic modeling of robot arm and a potent solution for the control strategy of robot arm. [ABSTRACT FROM AUTHOR]

Flemingia macrophylla has traditionally been applied to relieve inflammation, diabetes, and circulatory complications. The leaf extract of F. macrophylla and its fractions were investigated for their in-vitro antioxidant and anti-diabetic properties. The phytochemical screening showed valuable phytochemicals, including glycosides, flavonoids, saponins, etc. GC-MS analysis of the phytochemicals in the methanol extract detected 19 bioactive compounds. Among the diverse fractions, the ethyl acetate fraction (EFM) exhibited the highest phenol and flavonoid contents of 557 mg GAE/g and 326 mg QCE/g, respectively. The total antioxidant content of EFM was found to be 292.41±19.16 mg AAE/g, while its antidiabetic study showed the greatest level of α -glucosidase (IC50: 11.27±1.25 µg/mL) and α -amylase (IC50: 10.04±0.63 µg/mL) inhibitory effects. The docking results showed that C6 had the highest binding scores of -9.0, -7.4, and -7.6 kcal/mol against antioxidant (6NGJ), α-glucosidase (5NN5), and α-amylase (4GQR) proteins, respectively. The dynamics simulation disclosed that C6-receptor protein complexes remained stable at the binding pocket under human body conditions and retained their stiff morphology for 100 nanoseconds (ns). ADMET results demonstrated their noncarcinogenic and well-absorbed properties, where PASS prediction data confirmed their efficacy as an antioxidant, antiulcerative, thrombolytic, and antidiabetic. Therefore, F. macrophylla has potential health benefits. [ABSTRACT FROM AUTHOR]

This research introduces the NeuRaiSya (Neural Railway System Application), an innovative railway signaling system integrating deep learning for passenger analysis. The objectives of this research are to simulate the NeuRaiSya and evaluate its effectiveness using the GreatSPN tool (graphical editor for Petri nets). GreatSPN facilitates evaluations of system behavior, ensuring safety and efficiency. Five models were designed and simulated using the Petri nets model, including the Dynamics of Train Departure model, Train Operations with Passenger Counting model, Timestamp Data Collection model, Train Speed and Location model, and Train Related-Issues model. Through simulations and modeling using Petri nets, the study demonstrates the feasibility of the proposed NeuRaiSya system. The results highlight its potential in enhancing railway operations, ensuring passenger safety, and maintaining service quality amidst the evolving railway landscape in the Philippines. [ABSTRACT FROM AUTHOR]